Evidence map›Paper›PMID 40045413›Full record

Trial reportBMC psychology2025

Preliminary effects of mobile computerized cognitive training in adults with mild cognitive impairment: interim analysis of a randomized controlled trial.

Drin Ferizaj, Oskar Stamm, Luis Perotti, Eva Maria Martin, Kathrin Finke, Carsten Finke, Tilo Strobach, Anika Heimann-Steinert

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BMC psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Drin FerizajDepartment of Geriatrics and Medical Gerontology (Forschungsgruppe Geriatrie), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Reinickendorfer Straße 61, Haus 7, 2. OG, Berlin, 13347, Germany. drin.ferizaj@charite.de.ORCID http://orcid.org/0000-0002-7132-7778
Oskar StammDepartment of Geriatrics and Medical Gerontology (Forschungsgruppe Geriatrie), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Reinickendorfer Straße 61, Haus 7, 2. OG, Berlin, 13347, Germany.ORCID http://orcid.org/0000-0003-1584-687X
Luis PerottiDepartment of Geriatrics and Medical Gerontology (Forschungsgruppe Geriatrie), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Reinickendorfer Straße 61, Haus 7, 2. OG, Berlin, 13347, Germany.ORCID http://orcid.org/0000-0003-0020-2617
Eva Maria MartinMemory Center, Department of Neurology, Jena University Hospital, Jena, Germany.ORCID http://orcid.org/0009-0004-4840-4263
Kathrin FinkeMemory Center, Department of Neurology, Jena University Hospital, Jena, Germany.ORCID http://orcid.org/0000-0001-8546-7141
Carsten FinkeDepartment of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Sauerbruchweg 5, Berlin, 10117, Germany.ORCID http://orcid.org/0000-0002-7665-1171
Tilo StrobachDepartment of Psychology, ICAN Institute for Cognitive and Affective Neuroscience, Medical School Hamburg, Am Kaiserkai 1, Hamburg, 20457, Germany.
Anika Heimann-SteinertDepartment of Geriatrics and Medical Gerontology (Forschungsgruppe Geriatrie), Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Reinickendorfer Straße 61, Haus 7, 2. OG, Berlin, 13347, Germany.ORCID http://orcid.org/0000-0001-8025-266X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computerized cognitive training (cCT) is a non-invasive treatment strategy in which individuals repeatedly practice computer-based tasks targeting specific cognitive functions. While traditional face-to-face cognitive training is costly and accompanied by long waiting times, mobile cCT can improve the healthcare situation due to its accessibility and versatility. This interim analysis of the NeuroNation MED Effectiveness Study (NeNaE) explores the initial effects of a mobile, gamified cCT (NeuroNation MED) on cognitive and psychosocial outcomes in adults diagnosed with mild cognitive impairment (MCI; ICD-10 code F06.7). In the intention-to-treat analysis, the intervention group (IG) performed 12 weeks of training with the NeuroNation MED app, while the control group (CG) served as a waiting group. This interim analysis included the first 50 participants (IG: n = 36; CG: n = 14). The primary outcome was the index score of the Neuropsychological Assessment Battery Screening Module (S-NAB). Alpha spending resulted in an alpha level of 0.00305 for this interim analysis. This analysis provided preliminary evidence suggesting potential benefits of the intervention, with the IG demonstrating a significant improvement in the S-NAB index score (t(35) = 3.17, p = 0.0028, Cohen's d = 0.53). However, ANCOVA revealed no significant group differences between IG and CG in the S-NAB index score (F(1, 47) = 5.39, p = 0.025, η

Indexed as

Cognitive Behavioral TherapyCognitive DysfunctionMobile ApplicationsTherapy, Computer-AssistedAgedCognitive TrainingFemaleHumansMaleMiddle AgedNeuropsychological TestsTreatment OutcomeCognitive trainingComputerized trainingMild cognitive impairmentMobile interventionRandomized controlled trial

Identifiers

PMID40045413
PMCPMC11881253

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.